About EPIC:
EPIC is a data visualization app that was created by Nike and the digital agency R/GA. During the 2011 NBA Playoffs, this visualization app collects tweets about Nike sponsored NBA players per hour. On the pages of the visualization, the data collected from the tweets organizes the players in a grid map, based on the number of tweets received per hour. Not only does it calculate the number of tweets for each player but also the number of tweets about each team during the playoffs.
Within the visualization there are two options for mode and view. For mode, you can choose between player and game and for view, it is between athlete or “kicks” (also known as shoes) to view what has been most tweeted about. And if you click on a player, you also can view historical stats about them, up-to-date information, what shoes each play
Figure 1: Player profile of JJ Redick
er is wearing during the game, what is each player’s speciality, any photos and videos that Nike uploads on that player, and the option of “liking” the player or shoe (Figure 1).
Since the visualization is created by Nike, the intended audience is for Nike consumers. A general basketball fan is also the intended audience but due to the fact that the data collected is based on Nike sponsored players, the target audience can be narrowed to those who are fans of both the NBA and Nike.
Strengths:
A good feature about this visualization is that it is live, so you are seeing real-time
Figure 2: Pre-made tweet
information being received. That can tell you what or who is being most talked about during a game. Another good feature is that because it uses Twitter feeds, one is able to interact with others, using their Smartphone, based on the data given by the app while watching the game. The visualization allows you to tweet directly from it; you choose the player or “kicks” you would like to tweet about and a pre-made tweet is ready to be sent to your Twitter feed (Figure 2). Thus, it is an interactive visualization.
The visualization app also uses a good marketing strategy within the “kicks” area. If you select a player and view what shoes the player you see it, you like it and giving you the option to purchase right there, adds some pressure to actually want to buy it, especially if the shoe has been tweeted about a lot. This is also a good use of branding.wore during the game, there is a link directing you to purchase the shoe, if you like it (Figure 3). It is essentially a call-to-action strategy, where if
Another good feature is that the visualization is easy to navigate through; there are two modes and two views. The fact that it organizes the data in a grid map makes the visualization easier to read. As well, one doesn’t only have to read the number of tweets a player received per hour but the size of the image of the player reports that information. And to easily access a player or team’s information, you can search for it.
Figure 3: The "kicks" of players.
Weaknesses:
There is an option of viewing this for the WNBA but it doesn’t appear to be updated which I feel it is unnecessary to have that option if nothing would be updated.
Using a grid map to organize the data is a good method of demonstrating what/who has received the most tweets but there are a few cases where it is difficult to read the position of each player. In Figure 4, one of the images is portrait sized which shifts the organization and it becomes difficult to tell where the line continues. One way to improve this is if there was a text box for each player with the number of tweets they received per hour – the number is only shown for the top 10 players.
Is the visualization effective?
Overall, I think that this visualization does effectively communicate what it wants to achieve. The main purpose of this visualization is to show which player is being most tweeted about during the playoffs and it shows exactly just that when one first views the visualization. It does so using three different ways: showing the value of tweets the player receives, communicating the same information
Figure 4: Organization in a grid map form.
by the size of the player’s image and organizing that information in a grid map.
Therefore, using three methods helps to further reiterate the same piece of information without causing chaos to the user that helps achieve the goal of the visualization.
Nike's EPIC
Synthia TruongAbout EPIC:
EPIC is a data visualization app that was created by Nike and the digital agency R/GA. During the 2011 NBA Playoffs, this visualization app collects tweets about Nike sponsored NBA players per hour. On the pages of the visualization, the data collected from the tweets organizes the players in a grid map, based on the number of tweets received per hour. Not only does it calculate the number of tweets for each player but also the number of tweets about each team during the playoffs.
Within the visualization there are two options for mode and view. For mode, you can choose between player and game and for view, it is between athlete or “kicks” (also known as shoes) to view what has been most tweeted about. And if you click on a player, you also can view historical stats about them, up-to-date information, what shoes each play
Since the visualization is created by Nike, the intended audience is for Nike consumers. A general basketball fan is also the intended audience but due to the fact that the data collected is based on Nike sponsored players, the target audience can be narrowed to those who are fans of both the NBA and Nike.
Strengths:
A good feature about this visualization is that it is live, so you are seeing real-time
information being received. That can tell you what or who is being most talked about during a game. Another good feature is that because it uses Twitter feeds, one is able to interact with others, using their Smartphone, based on the data given by the app while watching the game. The visualization allows you to tweet directly from it; you choose the player or “kicks” you would like to tweet about and a pre-made tweet is ready to be sent to your Twitter feed (Figure 2). Thus, it is an interactive visualization.
The visualization app also uses a good marketing strategy within the “kicks” area. If you select a player and view what shoes the player you see it, you like it and giving you the option to purchase right there, adds some pressure to actually want to buy it, especially if the shoe has been tweeted about a lot. This is also a good use of branding.wore during the game, there is a link directing you to purchase the shoe, if you like it (Figure 3). It is essentially a call-to-action strategy, where if
Another good feature is that the visualization is easy to navigate through; there are two modes and two views. The fact that it organizes the data in a grid map makes the visualization easier to read. As well, one doesn’t only have to read the number of tweets a player received per hour but the size of the image of the player reports that information. And to easily access a player or team’s information, you can search for it.
There is an option of viewing this for the WNBA but it doesn’t appear to be updated which I feel it is unnecessary to have that option if nothing would be updated.
Using a grid map to organize the data is a good method of demonstrating what/who has received the most tweets but there are a few cases where it is difficult to read the position of each player. In Figure 4, one of the images is portrait sized which shifts the organization and it becomes difficult to tell where the line continues. One way to improve this is if there was a text box for each player with the number of tweets they received per hour – the number is only shown for the top 10 players.
Is the visualization effective?
Overall, I think that this visualization does effectively communicate what it wants to achieve. The main purpose of this visualization is to show which player is being most tweeted about during the playoffs and it shows exactly just that when one first views the visualization. It does so using three different ways: showing the value of tweets the player receives, communicating the same information
Therefore, using three methods helps to further reiterate the same piece of information without causing chaos to the user that helps achieve the goal of the visualization.
References:
"Nike Basketball - Epic - Nike Family: Live - US." Nike. Web. 02 Nov. 2011. <http://www.nike.com/nikeos/p/nikebasketball/en_US/epic>.
Wasserman, Todd. "How Nike Stepped Up Its Social Media Game for the NBA Playoffs."Mashable.com. Mashable, 13 June 2011. Web. 02 Nov. 2011. <http://mashable.com/2011/06/13/nike-social-media-nba-playoffs/>.